Head of Ray Core / Ray Ecosystem ( Director of Engineering)

About Anyscale:At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world.With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert.Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date.About the role:Ray Core is the foundational distributed runtime at the heart of Ray. It is responsible for cluster scheduling, distributed execution, fault tolerance, resource management, and the APIs that higher-level Ray libraries and ecosystem projects are built upon.We are looking for a Director of Engineering to lead the Ray Core Engineering organization / Ray OSS Ecosystem. This role owns the technical and organizational direction of one of the most critical components of Ray and plays a central role in shaping Ray as long-term infrastructure used across the ML and data ecosystem.This is a deeply technical leadership role. You will partner closely with senior engineers, researchers, and product leaders, and you will be expected to engage meaningfully in systems design, architectural decisions, and technical tradeoffs.What You’ll Do:Lead and grow a team of senior engineers working on Ray Core and adjacent ecosystem componentsAct as a technical leader in the open-source Ray community, setting standards for design, quality, and collaboration. Own the growth and adoption of OSS RayOwn the technical vision and roadmap for Ray’s distributed runtime, including:cluster scheduling and resource managementdistributed execution and control-plane architecturefault tolerance, recovery, and correctnessperformance, scalability, and efficiencyDrive high-quality systems design and architecture, including RFCs, design reviews, and long-term API strategyEnsure Ray Core continues to scale across:larger clusters and heterogeneous hardwareincreasingly diverse workloads (ML, data, agents, serving)a growing open-source user and contributor basePartner cross-functionally with product, research, and go-to-market teams to align technical execution with company strategyDevelop and mentor engineering leaders and senior ICs, fostering a strong culture of technical excellence and ownershipWhat We’re Looking For:8+ years of software engineering experience, with significant time spent building distributed systems or systems infrastructure5+ years of experience leading and scaling engineering teams, ideally including managersStrong background in one or more of:distributed systems and/or databasesschedulers, runtimes, or control planescloud infrastructure or large-scale backend systemsDeep understanding of systems fundamentals such as:concurrency and parallelismfault tolerance and consistencyperformance and resource isolationExperience working with or leading open-source software (as a maintainer, contributor, or heavy user)Ability to operate as a player-coach: comfortable diving into technical details while leading at the organizational levelStrong communication skills and a track record of making sound technical tradeoffs in complex systemsNice to Have:Experience with Ray, Spark, Kubernetes, or similar distributed frameworksBackground in ML systems, data systems, or large-scale compute platformsExperience leading teams responsible for widely used, long-lived APIsWhy Anyscale:Own and shape a foundational distributed system used by thousands of teamsWork on hard, meaningful systems problems at scaleLead in a strong open-source culture with real-world impactCollaborate with an exceptional team of deeply technical e ... (truncated, view full listing at source)